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Methods for extracting place semantics from Flickr tags
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ACM Transactions on the Web (TWEB) archive
Volume 3 ,  Issue 1  (January 2009) table of contents
Article No. 1  
Year of Publication: 2009
ISSN:1559-1131
Authors
Tye Rattenbury  Intel Corporation, Santa Clara, CA
Mor Naaman  Rutgers University, New Brunswick, NJ
Publisher
ACM  New York, NY, USA
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ABSTRACT

We describe an approach for extracting semantics for tags, unstructured text-labels assigned to resources on the Web, based on each tag's usage patterns. In particular, we focus on the problem of extracting place semantics for tags that are assigned to photos on Flickr, a popular-photo sharing Web site that supports location (latitude/longitude) metadata for photos. We propose the adaptation of two baseline methods, inspired by well-known burst-analysis techniques, for the task; we also describe two novel methods, TagMaps and scale-structure identification. We evaluate the methods on a subset of Flickr data. We show that our scale-structure identification method outperforms existing techniques and that a hybrid approach generates further improvements (achieving 85% precision at 81% recall). The approach and methods described in this work can be used in other domains such as geo-annotated Web pages, where text terms can be extracted and associated with usage patterns.


REFERENCES

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1
 
2
Aipperspach, R., Rattenbury, T., Woodruff, A., and Canny, J. 2006. A quantitative method for revealing and comparing places in the home. In Proceedings of the International Conference on Ubiquitous Computing (Ubicomp). Springer.
3
4
 
5
Arampatzis, A., van Kreveld, M., Reinbacher, I., Clough, P., Joho, H., Sanderson, M., Jones, C. B., Vaid, S., Benkert, M., and Wolff, A. 2004. Web-Based delineation of imprecise regions. In Proceedings of the Workshop on Geographic Information Retrieval.
 
6
 
7
 
8
Brunsdon, C., Fotheringham, A., and Charlton, M. 2002. Geographically weighted summary statistics: A framework for localized exploratory data analysis. In Comput. Environm. Urban Syst. 26, 501--524.
 
9
 
10
Buyukokkten, O., Cho, J., Garcia-Molina, H., Gravano, L., and Shivakumar, N. 1999. Exploiting geographical location information of Web pages. In Proceedings of the Workshop on Web Databases (WebDB). Held in conjunction with ACM SIGMOD'99. http://dbpubs.stanford.edu/pub/1999-4.
11
12
 
13
14
15
 
16
17
18
 
19
 
20
 
21
Kruskal, J. B. 1956. On the shortest spanning subtree of a graph and the traveling salesman problem. In Proc. Amer. Math. Soc. 7, 1, 48--50.
 
22
Kulldorff, M. 1999. Spatial scan statistics: Models, calculations, and applications. In Scan Statistics and Applications, Glaz and Balakrishnan, eds., Springer, Boston, Birkhauser, 303--322.
23
 
24
McDowall, D., McCleary, R., Meidinger, E. E., and Jr., R. A. H. 1980. Interrupted Time Series Analysis. Sage University PaperSeries on Quantitative Applications in the Social Sciences.
 
25
Naaman, M., Paepcke, A., and Garcia-Molina, H. 2003. From where to what: Metadata sharing for digital photographs with geographic coordinates. In Proceedings of the 10th International Conference on Cooperative Information Systems (CoopIS). Springer, Berlin, 196--217.
 
26
Ng, A., Jordan, M., and Weiss, Y. 2001. On spectral clustering: Analysis and an algorithm. In Advances in Neural Information Processing Systems. Vol. 14.
 
27
Openshaw, S. 1984. The Modifiable Areal Unit Problem: Concepts and Techniques in Modern Geography. Geo Books, Norwich.
 
28
Openshaw, S., Charlton, M., Wymer, C., and Craft, A. 1987. A mark 1 geographical analysis machine for the automated analysis of point data sets. Int. J. Geograph. Inf. Syst. 1, 4, 335--358.
 
29
Purves, R., Clough, P., and Joho, H. 2005. Identifying imprecise regions for geographic information retrieval using the web. In Proceedings of the Conference GISRUK.
30
 
31
Sarin, S., Nagahashi, T., Miyosawa, T., and Kameyama, W. 2007. Exploiting users' personal and public information for personal photo annotation. In Proceedings of the IEEE International Conference on Multimedia. IEEE, 564--567.
 
32
Schmitz, P. 2006. Inducing ontology from Flickr tags. In Proceedings of the Workshop on Collaborative Web Tagging at WWW2006.
33
34
35
 
36
Witkin, A. 1983. Scale space filtering. In Proceedings of the International Joint Conference on Artificial Intelligence.
37
38

Collaborative Colleagues:
Tye Rattenbury: colleagues
Mor Naaman: colleagues